A geographic information system is an information system designed to work with data referenced by spatial or geographic coordinates. For example, on a very basic level, a contour map of an area of land (that is, a map in which contour lines indicate the elevations at specific geographic points) could be considered a GIS. If, to the contour map, we added a street map, a sewer map, and an aerial photograph, then we would have a GIS composed of four data sets: each set being referred to as a data layer or data plane.
In an automated GIS, the data layers will be stored in a data base system and a set of tools will be included to enter, manipulate and analyze the data, and then display the result either on a screen or as hardcopy printout.
To create an automated GIS, it is necessary to first identify and gather data. Typical sources of such data are municipal maps, government survey maps, aerial photographs and other publicly available data sources. The data must be extracted from these sources and then be manipulated so that it may be entered into the GIS. In addition, the data must be georegistered or georeferenced. That is, the spatial data must be referenced to a coordinate system such as Universal Transverse Mercator, State Plane, or Latitude/Longitude.
The geo-registration process is mathematically as follows: EQU x=f.sub.1 (X,Y) EQU y=f.sub.2 (X,Y)
where
(x,y)=distorted coordinates in some coordinate system, PA1 (X,Y)=correct coordinates in a selected reference grid PA1 f.sub.1, f.sub.2 =transformation functions PA1 1. select a point from the spatial data available (distorted coordinate system) and determine the equivalent point in the selected reference grid; PA1 2. express both selected points in terms of pairs of coordinates and compute the transformation function which reflects the relationship between the pairs; PA1 3. choose another point and repeat steps 1 and 2.
In its simplest form, where the distorted coordinates are taken from a scale drawing and the selected reference grid is a flat surface marked by latitude and longitude, the transformation functions are linear equations of the type: x=AX+BY+C, where A, B and C are constants. In the case of aerial photographs, where the intent is to represent the curved earth surface on a flat map, and where the angle of the photograph, as well as the photographs representation of a curved surface in a two dimensional plane must be taken into account, the transformations are considerably more complex but are well known in the art.
The standard method by which data is georegistered against selected reference coordinates (i.e. of identifying the required transformation functions) can be described as follows:
Repeating the process for all points in the spatial data set would be prohibitively costly in both time and effort. Accordingly, the process is repeated only for a selected sample of points. The method by which the points are chosen (the sampling methodology) can be taken from a variety of well-known techniques such as nearest neighbor, bilinear, or cubic convolution.
It is not uncommon for the "true" transformation function to vary over the area of interest. For example, in an aerial photograph, the curvature of the earth results in a different mapping of points to the two dimensional picture. Accordingly, the "true" transformation function varies depending on the distance from the observation point to the pictured surface. As another example, consider a diagram of water mains. If the purpose of the diagram was to indicate the points of interconnection, then the representation of the mains between such interconnection points would not necessarily be consistant in the sense that there would likely not be a constant ratio of mapped lines to the physical distance between points. The "true" transformation function to georeference such a diagram would consist of a collection of linear functions, none of which were necessarily related to any other.
Where the "true" transformation varies over different parts of a map, the transformation calculated from only a subset of points may have certain inaccuracies. This will result in distortions when the calculated transformation function is used to georeference the entire set of spacial data points.
Various schemes for automating the process of georeferencing exist in the art. Most of the techniques focus on reducing the distortion by choosing a large number of coordinate pairs (i.e. rubber-sheeting techniques.) The current state of the art is described in the book Remote Sensing and Image interpretation, Lillesand and Kiefer, Second edition, 1987, Chapter 10, Section 10.2.
Often GIS users require information embodied in data in more than one GIS. Since each GIS typically keeps its data in a proprietary format, there are very few commercially available conversion programs which allow a user to import data from one or more source GISs to a single target GIS.
In the prior art, conversion from one GIS to another was done by taking the physical output of each of the required data layers that resided in one GIS and mapping that output onto the second GIS. To describe this process more specifically, the following notation will be used: Data Layer (a,b) will refer to a bth layer of GISa. Accordingly, assume that a user wishes to use Data Layer (1,1), Data Layer (1,2), and Data Layer (1,3), all of which are found in GIS1, together with Data Layer (2,1) which is found in GIS2. Further assume that GIS2 contains a particularly useful data manipulation tool so that it is mandatory that the GIS1 Data Layers (1,n) be converted to GIS2, rather than the more simple step of converting Data Layer (2,1) to GIS1 format.
In this situation, the user would take the spatial information of Data Layer (1,1) (typically by using the tools of GIS1 to create a graphic output such as a physical map) and georegistering this information against Data Layer (2,1), using the same techniques that would have been used had Data Layer (1,1) and Data Layer (2,1) been a surveyor map and a desired coordinate system, respectively. (In other words, using the techniques described in the preceding paragraphs.) This process would be repeated for Data Layer (1,2) and Data Layer (1,3).
Since each of the Data Layers (1,n) contained different data, (different points and lines would be represented on the map associated with each Layer), the set of points the user selected from Data Layer (1,1) to register against points from Data Layer (2,1) would necessarily be different from the set chosen from Data Layer (1,2) to be registered against Data Layer (2,1). This means that the time-consuming process of repeatedly choosing different coordinate pairs must be executed for each layer. Further, as previously discussed, the choice of a particular subset of coordinate pairs can introduce certain distortions in the georegistration. Since the sets of coordinates were different for each Data Layer (1,n), the distortions in the georegistration would be different for each layer. This result is that the imported Layers would be registered imperfectly and would not overlay properly.